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To confront the challenges posed by air pollution and climate change, China has undertaken significant initiatives to develop strategies that address both issues concurrently. However, the health benefits of these initiatives have not been clearly articulated. In this study, the dynamic changes in health impacts under air pollution and carbon reduction actions in China are evaluated by employing the latest concentration-response models and projected PM 2.5 concentrations under future scenarios. From 2020 to 2060, the enforcement of clean air and climate mitigation policies is expected to increase the percentage of the population living with PM 2.5 concentrations meeting the 10 μg/m 3 standard by 79 %. Without the implementation of relevant mitigation measures, PM 2.5 -associated deaths are projected to double due to an aging population. In comparison to the 2060 reference scenario, the joint implementation of clean air and carbon neutrality measures is expected to reduce nationwide PM 2.5 -associated mortality by 62 %, equivalent to 2.15 (95 % CI: 1.80-2.48) million deaths. Stringent pollution controls are crucial for reducing PM 2.5 -associated deaths before 2030, after which carbon neutrality actions become increasingly significant from 2030 to 2060. The challenges of mitigating future PM 2.5 -associated deaths vary greatly across regions, showing a critical response to pollution control and carbon reduction. The research proves the effectiveness of China's future air pollution control and carbon reduction policies in mitigating PM 2.5 -associated deaths., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Central environmental protection inspections have completed their goal of full coverage of 31 provinces in China, and more than 17,000 officials have been held accountable. The media has evaluated the effectiveness of central environmental protection inspections using the notions of "instant results" and the "miracle drug of environmental governance." Can this approach effectively promote local environmental governance? This paper takes the treatment effect of central environmental protection inspections on air pollution as an example. Using the method of regression discontinuity, central environmental protection inspections are found to have a positive effect on the air quality index (AQI), but this effect is only short term and unsustainable. Additionally, there are inter-provincial differences. Judging from the research results on sub-contaminants, the treatment effect of central environmental protection inspections on air pollution is mainly reflected in PM 10 , PM 2.5 and CO. Under the current situation in which PM 10 and PM 2.5 are the main assessment indexes, this phenomenon indicates that due to the political achievements and promotion of local officials and for reasons of accountability, it is more effective for the central government to conduct specific environmental assessments through local governments than to conduct central environmental protection inspections.

Since air pollution is an important factor hindering China's economic development, China has passed a series of bills to control air pollution. However, we still lack an understanding of the status of environmental efficiency in regard to air pollution, especially PM 2.5 (diameter of fine particulate matter less than 2.5 μm) pollution. Using panel data on ten major Chinese city groups from 2004 to 2016, we first estimate the environmental efficiency of PM 2.5 by epsilon-based measure (EBM) meta-frontier model. The results show that there are large differences in PM 2.5 environmental efficiency between cities and city groups. The cities with the highest environmental efficiency are the most economically developed cities and the city group with the highest environmental efficiency is mainly the eastern city group. Then, we use the meta-frontier Malmquist EBM model to measure the meta-frontier Malmquist total factor productivity index (MMPI) in each city group. The results indicate that, overall, China's environmental total factor productivity declined by 3.68% and 3.49% when considering or not the influence of outside sources, respectively. Finally, we decompose the MMPI into four indexes, namely, the efficiency change (EC) index, the best practice gap change (BPC) index, the pure technological catch-up (PTCU) index, and the frontier catch-up (FCU) index. We find that the trend of the MMPI is consistent with those of the BPC and PTCU indexes, which indicates that the innovation effect of the BPC and PTCU indexes are the main driving forces for productivity growth. The EC and FCU effect are the main forces hindering productivity growth.

Urbanization and industrialization have spurred air pollution, making it a global problem. An understanding of the spatiotemporal characteristics of PM 2.5 and PM 10 concentrations (particulate matter with an aerodynamic diameter of less than 2.5 μm and 10 μm, respectively) is necessary to mitigate air pollution. We compared the characteristics of PM 2.5 and PM 10 concentrations and their trends of China, India, and the U.S. from 2014 to 2017. Particulate matter levels were lowest in the U.S., while China showed higher concentrations, and India showed the highest. Interestingly, significant declines in PM 2.5 and PM 10 concentrations were found in some of the most polluted regions in China as well as the U.S. No comparable decline was observed in India. A strong seasonal trend was observed in China and India, with the highest values occurring in winter and the lowest in summer. The opposite trend was noted for the U.S. PM 2.5 was highly correlated with PM 10 for both China and India, but the correlation was poor for the U.S. With regard to reducing particulate matter pollutant concentrations, developing countries can learn from the experiences of developed nations and benefit by establishing and implementing joint regional air pollution control programs.

Transboundary air pollution is a global environmental and public health problem including in the U.S., where pollution emissions from China, the largest emitter of anthropogenic air pollution in the world, can travel across the Pacific Ocean and reach places like California and Oregon. We examine the effects of transboundary air pollution following major events in China, specifically sandstorms, a natural-occurring source of air pollution, and Chinese New Year, a major 7-day holiday, on background air quality in the U.S. We focus on high elevation sites on the west coast between 2000 and 2013. We use regression analysis and a natural experiment to exploit the variation in the timing of these events in China, which are plausibly uncorrelated to other factors that affect air quality in China and the U.S. We find that sandstorms are associated with statistically significant increases in background coarse and fine particulate matter (PM) in the U.S., representing between 16 and 39% of average weekly PM levels. We also find Chinese New Year is associated with modest reductions in background air quality in the U.S., representing between 0.4 and 2.5% of PM levels. Findings are robust to different models and falsification tests. These results suggest that regression analysis could be a powerful tool to complement other, more widely used techniques in the environmental sciences that study this problem. This also has important implications for policymakers, who could track major sandstorms in China and prepare for possible increased foreign pollution emissions in the U.S. [ABSTRACT FROM AUTHOR]

There are concerns that the reported association of ambient fine particulate matter (PM2.5) with mortality might be a mixture of PM2.5 and weather conditions. We evaluated the effects of extreme weather conditions and weather types on mortality as well as their interactions with PM2.5 concentrations in a time series study. Daily non-accidental deaths, individual demographic information, daily average PM2.5 concentrations and meteorological data between 2012 and 2014 were obtained from Shanghai, China. Days with extreme weather conditions were identified. Six synoptic weather types (SWTs) were generated. The generalized additive model was set up to link the mortality with PM2.5 and weather conditions. Parameter estimation was based on Bayesian methods using both the Jeffreys’ prior and an informative normal prior in a sensitivity analysis. We estimate the percent increase in non-accidental mortality per 10 μg/m3 increase in PM2.5 concentration and constructed corresponding 95% credible interval (CrI). In total, 336,379 non-accidental deaths occurred during the study period. Average daily deaths were 307. The results indicated that per 10 μg/m3 increase in daily average PM2.5 concentration alone corresponded to 0.26–0.35% increase in daily non-accidental mortality in Shanghai. Statistically significant positive associations between PM2.5 and mortality were found for favorable SWTs when considering the interaction between PM2.5 and SWTs. The greatest effect was found in hot dry SWT (percent increase = 1.28, 95% CrI: 0.72, 1.83), followed by warm humid SWT (percent increase = 0.64, 95% CrI: 0.15, 1.13). The effect of PM2.5 on non-accidental mortality differed under specific extreme weather conditions and SWTs. Environmental policies and actions should take into account the interrelationship between the two hazardous exposures. [ABSTRACT FROM AUTHOR]

China’s tremendous economic growth in the past three decades has resulted in a number of environmental problems, including the deterioration of air quality. In particular, fine particulate matter (PM) has received increasing attention from scientists, governmental agencies, and the public due to its adverse impacts on human health. Monitoring the spatiotemporal patterns of air pollution is important for understanding its transport mechanisms and making effective environmental policies. The main goal of this study, therefore, was to quantify the spatial patterns and movement of air pollution in China at annual, daily, and hourly scales, so that the underlying drivers could be better understood. We used remote sensing data and landscape metrics together to capture spatiotemporal signatures of air pollution. Our results show that, at the annual scale, PM 2.5 concentrations in China increased gradually from 1999 to 2011, with the highest concentrations occurring in the North China Plain as well as the middle and lower reaches of the Yangtze River Basin. The total population affected by air pollution was about 975 million in 2010 (about 70% of China’s population). Our more detailed analysis on daily and hourly scale further revealed that a heavy air pollution event occurred, expanded, aggregated, and finally dissipated over Northern China during Oct. 6–12, 2014, suggesting that the Beijing-Tianjin-Hebei region a center of severe pollution. Crop stalks burning in agricultural areas in this region seemed to be one of the leading drivers, along with coal burning and transportation emissions. Our study demonstrates that spatial pattern analysis with landscape metrics is effective for analyzing source-sink dynamics of air pollution and its potential drivers. Our findings of major source areas and movement trajectories should be useful for making air pollution control policies to improve China’s air quality. [ABSTRACT FROM AUTHOR]

Burning coal for winter heating has been considered a major contributor to northern China's winter haze, with the district heating boilers holding the balance. However a decade of intensive efforts on district heating boilers brought few improvements to northern China's winter air quality, arousing a speculation that the household heating stoves mainly in rural area rather than the district heating boilers mainly in urban area dominate coal emissions in winter. This implies an extreme underestimation of rural household coal consumption by the China Energy Statistical Yearbooks (CESYs), although direct evidence supporting this speculation is lacking. A village energy survey campaign was launched to gather the firsthand information on household coal consumption in the rural areas of two cities, Baoding (in Hebei province) and Beijing (the capital of China). The survey data show that the rural raw coal consumption in Baoding (5.04 × 10 3 kt) was approximately 6.5 times the value listed in the official CESY 2013 and exceeded the rural total of whole Hebei Province (4668 kt), revealing a huge amount of raw coal missing from the current statistical system. More importantly, rural emissions of particulate matter (PM) and SO 2 from raw coal, which had never been included in widely distributing environmental statistical reports, were found higher than those from industrial and urban household sectors in the two cities in 2013, which highlights the importance of rural coal burning in creating northern China's heavy haze and helps to explain why a number of modeling predictions on ambient pollutant concentrations based on normal emission inventories were more bias-prone in winter season than in other seasons. We therefore recommend placing greater emphasis on the “missing” rural raw coal to help China in its long-term ambition to achieve clean air in the context of rapid economic development. [ABSTRACT FROM AUTHOR]

Air deterioration caused by pollution has harmed public health. The existing studies on the economic loss caused by a variety of air pollutants in multiple cities are lacking. To understand the effect of different pollutants on public health and to provide the basis of the environmental governance for governments, based on the dose-response relation and the willingness to pay, this paper used the latest available data of the inhalable particulate matter (PM) and sulphur dioxide (SO) from January 2015 to June 2015 in 74 cities by establishing the lowest and the highest limit scenarios. The results show that (1) in the lowest and highest limit scenario, the health-related economic loss caused by PM and SO represented 1.63 and 2.32 % of the GDP, respectively; (2) For a single city, in the lowest and the highest limit scenarios, the highest economic loss of the public health effect caused by PM and SO was observed in Chongqing; the highest economic loss of the public health effect per capita occurred in Hebei Baoding. The highest proportion of the health-related economic loss accounting for GDP was found in Hebei Xingtai. The main reason is that the terrain conditions are not conducive to the spread of air pollutants in Chongqing, Baoding and Xingtai, and the three cities are typical heavy industrial cities that are based on coal resources. Therefore, this paper proposes to improve the energy structure, use the advanced production process, reasonably control the urban population growth, and adopt the emissions trading system in order to reduce the economic loss caused by the effects of air pollution on public health. [ABSTRACT FROM AUTHOR]